From b03fb331f6a79d3a6f2a1afb261a6e747daaa63f Mon Sep 17 00:00:00 2001 From: Michael Waskom Date: Sun, 26 Jun 2022 22:34:34 -0400 Subject: [PATCH 1/2] Remove duplicated package information from setup.py --- setup.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/setup.py b/setup.py index a0211af8aa..98321f44b3 100644 --- a/setup.py +++ b/setup.py @@ -46,9 +46,6 @@ PACKAGES = [ 'seaborn', - 'seaborn._core', - 'seaborn._marks', - 'seaborn._stats', 'seaborn.colors', 'seaborn.external', 'seaborn._core', From d7088402ec06508cbbac6f48f3c658156b2f33b5 Mon Sep 17 00:00:00 2001 From: Michael Waskom Date: Mon, 27 Jun 2022 06:34:17 -0400 Subject: [PATCH 2/2] Add Python 3.10 classifier and update PyPI description --- setup.py | 27 +++++++++++++++++---------- 1 file changed, 17 insertions(+), 10 deletions(-) diff --git a/setup.py b/setup.py index 98321f44b3..811d125711 100644 --- a/setup.py +++ b/setup.py @@ -1,23 +1,29 @@ #! /usr/bin/env python # -# Copyright (C) 2012-2020 Michael Waskom +# Copyright (C) 2012-2022 Michael Waskom DESCRIPTION = "seaborn: statistical data visualization" LONG_DESCRIPTION = """\ -Seaborn is a library for making statistical graphics in Python. It is built on top of `matplotlib `_ and closely integrated with `pandas `_ data structures. + +Seaborn is a library for making statistical graphics in Python. It is built on +top of `matplotlib `_ and closely integrated with +`pandas `_ data structures. Here is some of the functionality that seaborn offers: - A dataset-oriented API for examining relationships between multiple variables -- Specialized support for using categorical variables to show observations or aggregate statistics -- Options for visualizing univariate or bivariate distributions and for comparing them between subsets of data -- Automatic estimation and plotting of linear regression models for different kinds dependent variables -- Convenient views onto the overall structure of complex datasets -- High-level abstractions for structuring multi-plot grids that let you easily build complex visualizations +- Flexible data aggregation with automatic estimation and plotting of error bars +- Multiple options for visualizing univariate or bivariate distributions +- Estimation and plotting of linear regression models to reveal trends +- Tools for building figures with multidimensional views onto complex dataset structure - Concise control over matplotlib figure styling with several built-in themes - Tools for choosing color palettes that faithfully reveal patterns in your data -Seaborn aims to make visualization a central part of exploring and understanding data. Its dataset-oriented plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. +Seaborn aims to make visualization a central part of exploring and understanding +data. Its dataset-oriented plotting functions operate on dataframes and arrays +containing whole datasets and internally perform the necessary semantic mapping +and statistical aggregation to produce informative plots. + """ DISTNAME = 'seaborn' @@ -46,11 +52,11 @@ PACKAGES = [ 'seaborn', - 'seaborn.colors', - 'seaborn.external', 'seaborn._core', 'seaborn._marks', 'seaborn._stats', + 'seaborn.colors', + 'seaborn.external', ] CLASSIFIERS = [ @@ -58,6 +64,7 @@ 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', 'Programming Language :: Python :: 3.9', + 'Programming Language :: Python :: 3.10', 'License :: OSI Approved :: BSD License', 'Topic :: Scientific/Engineering :: Visualization', 'Topic :: Multimedia :: Graphics',